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Biostatistics Advance Access published online on October 30, 2006
Biostatistics, doi:10.1093/biostatistics/kxl037
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© The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
Received October 11, 2005
Revised October 13, 2006
Accepted October 20, 2006

Article

Estimation of the benchmark dose by structural equation models

Esben Budtz-Jørgensen 1 *

1 Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, entr. B, P.O.Box 2099, DK-1014 Copenhagen K, Denmark; Institute of Public Health, University of Southern Denmark, Winslowparken 17, DK-5000 Odense C, Denmark

* To whom correspondence should be addressed.
Esben Budtz-Jørgensen, E-mail: ebj{at}biostat.ku.dk


  Abstract

While epidemiological data typically contain a multivariate response and often also multiple exposure parameters, current methods for safe dose calculations, including the widely used benchmark approach, rely on standard regression techniques. In practice, dose-response modeling and calculation of the exposure limit is often based on the seemingly most sensitive outcome. However, this procedure ignores other available data, it is inefficient and fails to account for multiple testing. Instead, risk assessment could be based on structural equation models, which can accommodate both a multivariate exposure and a multivariate response function. Furthermore, such models will allow for measurement error in the observed variables, which is a requirement for unbiased estimation of the benchmark dose. This methodology is illustrated with data on neurobehavioral effects in children prenatally exposed to methylmercury, where results based on standard regression models cause an underestimation of the true risk.

Keywords: environmental epidemiology; measurement error; multiple endpoints; risk assessment.
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